How to use python to calculate variance

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How to calculate the variance

Briefly show how the variance is calculated in pandas:

Official documents:

Def def_std (df): for ix,row in df.iterrows (): std = row.std () df.loc [ix, "std"] = std return dfPython to calculate variance, standard deviation, standard deviation

1. One of the measured values of the degree of dispersion

two。 The most commonly used measurements

3. Reflects the distribution of the data.

4. It reflects the average difference between the value and the mean of each variable.

5. Those calculated according to the overall data are called the total variance or standard deviation; those calculated according to the sample data are called the sample variance or standard deviation.

(the greater the standard deviation and variance, the greater the degree of discretization)

1. Variance

The variance describes the discreteness of the values of random variables to their mathematical expectations.

2. Standard deviation

Variance is the square of the data, which is too different from the detected value itself, so it is difficult for people to measure it intuitively, so the common open root of variance is converted back to what we want to call the standard deviation. Standard deviation has good mathematical properties. Comparatively speaking, it is the most widely used.

Standard deviation and Variance realization in Python

Import numpy as np arr = [1 arr_var 2, 3 arr_var 4 5] # find the variance arr_var = np.var (arr) # find the standard deviation arr_std = np.std (arr,ddof=1) print ("variance is:% f"% arr_var) print ("standard deviation is:% f"% arr_std)

Numpy: the overall (parent) standard deviation is calculated, and the parameter ddof = 0.

Pandas: the standard deviation of the sample is calculated, and the parameter ddof = 1.

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